To meet the surge in traffic demand and connectivity, radio technology for communication systems is gradually shifting towards a more flexible utilization of the available frequency spectrum at the network nodes forming the radio access network infrastructure, as well as toward denser deployments of low-powered network nodes with smaller coverage area.
In this context, the quality of experience of a user (e.g., in terms of average data rate) can be improved through more flexible and dynamic connections established with the network nodes having the potential and the resources to provide the desired service. Thus, user devices should be connected to network nodes that not necessarily provide the best signal strength but rather have more resources available or, equivalently, less traffic load per frequency resource.
To that end, we consider a system where network nodes are enabled to operate in or activate only portions of an available frequency band, hereafter referred to as frequency spectrum segments. In other words, a frequency band available at a network node is partitioned into a number of frequency spectrum segments. For instance, a frequency spectrum segment may be a portion or an entire component carrier of the 3GPP Long Term Evolution, LTE, system. In another example, a frequency spectrum segment may be a portion or the entire frequency band associated with a radio access technology (RAT) available at a network node. The frequency spectrum segments available at a network node may not necessarily be contiguous in the frequency domain nor have equal size (i.e., bandwidth). Further, the size of frequency spectrum segments at a network node can be static or dynamically configurable over time to adapt to e.g., load, traffic, demand or other network parameters related to frequency spectrum segments. The term available indicates that a frequency spectrum segment is a resource of a network node. Thus, a network node may autonomously determine, or may be configured to use/activate one or more frequency spectrum segments by which it can operate.
In this context, the utilization of frequency bands and RATS available at a network node can be adapted depending on the traffic/service demand, the type of traffic, the interference pattern, as well as the energy cost of operating with a larger portion of frequency spectrum or multiple RATs. In turn, the problem of controlling and making the utilization of spectrum flexible at the network side becomes a problem of associating/connecting user devices to frequency spectrum segment(s), and hence to the corresponding network node(s), that can provide the service desired by the user device, rather than assuring a connection to the network node that offers the best signal strength.
Thus, resource allocation methods for flexible spectrum utilization at the network nodes shall comprise more advanced cell-association and inter-frequency load balancing schemes that adapt the utilization of frequency spectrum at the network nodes so as to comply with users' traffic/service demands and network's energy costs.
In traditional cellular radio systems, user devices access the network by first searching synchronization signals transmitted by network nodes and measuring the strength of the associated reference signals, and then by transmitting an access request to the network node that provides the strongest received signal.
To this end, the user device receives as part of the broadcast channel a set of preamble sequences allowed to be used for initiating a random access with a network node. Thus, the random access (RACH) signal carries information specific to the network node that is intended to receive it. In response to this, the network node provides a temporary network identity to the user device, a time advance for uplink synchronization, and a set of time-frequency resources to be used to establish a radio bearer in the subsequent steps of the access procedure. Ultimately, a radio bearer is established and data can be exchanged.
Thus, conventional solutions require a user device to first detect the presence of a network by listening, decoding, and measuring the strength of downlink reference signals transmitted by network nodes. Then a user device attempts accessing the network at the network node that provides the best signal strength. This, however, does not guarantee the best usage of the network resources nor assures the best service to the users.
For instance, assuming a network node n applies an equal share of the available time-frequency radio resources to the served user devices, the theoretically achievable average user data rate can be modelled through the Shannon bound as
            r              m        ,        n              =                            W          n                          L          n                    ⁢                        log          2                ⁡                  (                      1            +                          S              ⁢                                                          ⁢              I              ⁢                                                          ⁢              N              ⁢                                                          ⁢                              R                                  m                  ,                  n                                                              )                      ,where Wn and Ln are the frequency bandwidth and the traffic load (e.g., expressed as the average number of active users served) of access node n, while SINRm,n is the signal to noise plus interference ratio experienced by user in from access node n.
It is clear from this equation that a network node n′ with lower traffic load Ln′<Ln can provide a higher average data throughput despite a worst signal strength (i.e., when SINRm,n′<SINRm,n).
While existing conventional solutions, such as the 3GPP Long Term Evolution Advanced (LTE-A) system, has addressed this issue for user devices already connected to the system, e.g., through mechanisms for balancing/shifting the traffic load among network nodes, there is currently no solution applicable to user devices not having a prior connection to the system.
In the mentioned conventional solutions, a user device assists the network in cell-association, handover and load balancing procedures by providing feedback related to the received signal strength from multiple network nodes. This, however, is insufficient to assure that the user device is connected or handed over to a network node with the potential to offer the required service.
A drawback of the related art is that upon detecting synchronization signals and measuring reference signals associated to one or multiple network node, a user device attempts to access the network at the network node offering the best signal strength, but not necessarily the best service. Related art systems, such as the 3GPP LTE, provide additional procedures to redirect or offload a user device to a better network node once a connection is established.
However, this requires additional system resources after the initial random access, and the overall procedure can require several hundreds of milliseconds before the user device is finally connected to the network node capable to provide the best service.
A second drawback of the related art is that it requires a user device to first search and detect the presence of the network, and not vice versa. Thus, a user device can select an access point for connecting to the network based on information related solely to the signal strength of a downlink reference signal. On the contrary, if the system had to make the decision by detecting the presence of a user device, and not vice versa, it would need more information to associate the user device to the best network node and frequency band.
Finally, the related art procedures to access a radio communication system do not scale well in the frequency domain, e.g., when access nodes can be configured to operate in multiple (eventually non-contiguous) frequency bands and with multiple radio access technologies.